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Field
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summary The PhD studentship will broadly explore development of cutting-edge AI solutions for image registration, anatomy segmentation, and immersive technology. The selected candidate will work with
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Research theme: Materials 4.0 No. of positions: 1 Open to: UK applicants This 3.5-year project is funded by the School of Natural Sciences and is available for home students; the successful
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aims: Develop end-to-end protocols for screening selected foods and nutraceuticals. Create advanced strategies for data integration using tailored algorithms and machine learning approaches. Demonstrate
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) in an appropriate discipline. Subject Area Computer Science & IT, Electrical & Electronic Keywords Artificial intelligence, floating-point arithmetic, numerical analysis, computer arithmetic, machine
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understanding of engineering mechanics and mechanical behaviour of materials. Knowledge of irradiation damage, computer modelling for nuclear materials, or steel metallurgy would be advantageous. Potential
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coding ability. Research Associate: Hold a PhD in Engineering, Mathematics or a closely related discipline, or equivalent research, industrial or commercial experience. *Candidates who have not yet been
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for the Science of Early Years and Youth at UEL A funded PhD position is available to work on a project exploring the impact of indoor and outdoor learning environments on children’s language and communication, and
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science or engineering discipline, possibly supported by an MSc Degree. Further information on English language requirements for EU/Overseas applicants . Funding Tuition fees + stipend are available
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group of 50 PhD students, 7 PDRAs and 24 academic staff. We are a friendly a social group and interact frequently on academic and non-academic matters. Feasibility: You will use established lab and
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in spin-dependent processes in materials and devices for energy technology. More information can be found on the group website: taitgroup.web.ox.ac.uk . Please contact Dr Claudia Tait (claudia.tait